Species' traits have been used both to explain and, increasingly, to predict species' vulnerability. Trait-based comparative analyses allow mechanisms causing vulnerability to be inferred and, ideally, conservation effort to be focused efficiently and effectively. However, empirical evidence of the predictive ability of trait-based approaches is largely wanting. I tested the predictive power of trait-based analyses on geographically replicated datasets of farmland bird population trends. I related the traits of farmland passerines with their long-term trends in abundance (an assessment of their response to agricultural intensification) in eight regions in two continents. These analyses successfully identified explanatory relationships in the regions, specifically: species faring badly tended to be medium-sized, had relatively short incubation and fledging periods, were longer distant migrants, had small relative brain sizes and were farmland specialists. Despite this, the models had poor ability to predict species' vulnerability in one region from trait-population trend relationships from a different region. In many cases, the explained variation was low (median R(2) = 8%). The low predictive ability of trait-based analyses must therefore be considered if such trait-based models are used to inform conservation priorities.